ArticleFrontiers in public health2025
A surge of AI-driven publications: the impact on health professionals and potential mitigating solutions.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Mapping risk communication practices in public health emergencies: a scoping review and comparison with Italian regional pandemic plans.BMC public health · 2026Article
- Scientific Publishing in the era of Artificial Intelligence: Integrity and Responsibility.Arquivos brasileiros de cardiologia · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid development of generative AI is reshaping scientific communication, particularly in medicine and public health. Since the release of ChatGPT in 2022, Large Language Models have become widely accessible, supporting manuscript editing, statistical analysis, and rapid evidence synthesis. However, this surge in AI-generated content raises concerns about the quality, reliability, and ethical implications of scientific publishing. Increased reliance on AI-driven authoring tools could exacerbate an "infodemic"-an overwhelming flood of potentially unreliable or misleading information. This risk is exacerbated by the prevailing "publish or perish" culture, which prioritizes publication volume over meaningful contributions. In addition, the proliferation of academic journals, especially those that charge high publication fees, deepens inequalities in global health research and limits access for low-income countries. Documented cases of fabricated articles and false authorship in predatory journals highlight how AI can be misused, threatening evidence-based medicine and influencing healthcare decisions. To address these challenges, regulatory frameworks, ethical guidelines, and widespread digital literacy training for researchers and health professionals are critical. A balanced approach-harnessing the efficiency of AI while safeguarding scientific integrity-is needed to prevent an AI-driven infodemic and ensure the equitable, high-quality dissemination of medical knowledge.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.